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This study introduces a new method for estimating ocean sediment sound speed by analyzing sound wave dispersion patterns. The technique accurately extracts modal frequencies and arrival times, improving upon previous filtering methods for long-range sound propagation.

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Area of Science:

  • Ocean acoustics
  • Geophysical signal processing
  • Acoustic inversion techniques

Background:

  • Accurate estimation of dispersion curves is crucial for understanding long-range sound propagation in ocean environments.
  • Current methods for dispersion tracking with sequential filtering have limitations that this study aims to address.

Purpose of the Study:

  • To develop and validate a novel sequential state-space method for extracting time-frequency information from received acoustic signals.
  • To estimate ocean sediment sound speed by analyzing the extracted dispersion patterns.
  • To improve upon existing dispersion tracking techniques.

Main Methods:

  • A sequential state-space method is developed, representing received fields as a sum of elemental pulses.
  • Time-frequency information is extracted using this novel approach.
  • Dispersion probability density functions are estimated via a particle filter for sound speed inversion.

Main Results:

  • The developed method accurately estimates dispersion curves from synthetic noisy data across various noise levels.
  • The approach demonstrates improved performance compared to previous sequential filtering techniques.
  • Challenges in correct mode identification for inversion are identified and solutions are discussed.

Conclusions:

  • The proposed method offers a robust way to extract time-frequency information for acoustic inversion in ocean environments.
  • This technique advances the capability to estimate sediment sound speed using dispersion patterns.
  • Addressing mode identification is key to successful sound speed inversion.